An improved gravitational search algorithm for solving an electromagnetic design problem

Publication Type:
Journal Article
Journal of Computational Electronics, 2020, 19, (2), pp. 773-779
Issue Date:
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© 2020, Springer Science+Business Media, LLC, part of Springer Nature. The gravitational search algorithm (GSA) is a novel optimization technique that relies upon the law of motion and law of gravity of masses to describe the interaction between the agents. The GSA has shown outstanding performance but suffers from the drawback of a slow process due to the dependence of the fitness function on the masses of the agents. As a result, after each iteration, the masses get heavier, restricting their movement. Due to this effect, the masses cancel out the gravitational forces on each other, preventing them from finding the optimum quickly. To overcome this limitation, an improved GSA based on a modified exploitation strategy is proposed herein. The primary aim of this modification is to enhance the performance of the algorithm in terms of faster convergence and avoidance of premature convergence. An electromagnetic optimization problem is used to validate the performance of the presented method. The simulation results confirm that the proposed method provides outstanding results in solving Loney’s solenoid design problem and that the stability of the solution is much better compared with those obtained using the standard gravitational search algorithm or various other state-of-the-art techniques that have previously been applied to solve this problem.
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